Master program: Computational Intelligence & Data Analytics (CIDA)

Computational Intelligence & Data Analytics is an area where knowledge is gained from large amounts of data.

The methods originate from very different areas of machine learning (ML) and data analysis, such as statistical learning theory, artificial intelligence, soft computing and others.

ML allows for a data-driven approach to develop systems that increasingly supplements or partially replaces a conventional model-driven approach. This means that data is analyzed, models are parameterized with data, and new types of applications are developed.

The very different application domains are, for instance, energy systems, automobiles, industrial automation, Internet of Things, marketing, quality control, or process control.

A successful application of ML methods requires on the one hand the careful and systematic handling of these methods, and on the other hand a kind of professional "creativity", i.e. the ability to generate innovation.

Subjects:

• Pattern Recognition & Machine Learning
• Data Analysis
• Artificial Intelligence
• Soft Computing

In the Master program CIDA, students attend different courses, whereby a minimum number of ECTS credits must be earned in each area:

1. Foundational Courses (area 1; basics of ML including data analysis, at least 12 ECTS-points),
2. Advanced Courses (area 2; advanced ML techniques and analysis methods, at least
   6 ECTS-points),
3. Lab Courses (area 3; teaching of more in-depth practical skills, at least 12 ECTS-points) and
4. Complementary Courses (area 4; either areas of application of ML or other foundational methods, at least 6 ECTS-points).

From the 12 remaining ECTS points in the master program, 6 must be earned in areas 1 or 2 and further 6 ECTS points in areas 3 or 4. This means that a total of at least 48 ECTS points must be achieved.

Some of the courses are offered in English.

Matching to the master program CIDA are also offer:

• Seminars
• Projects
• master theses